MFIC vs MFM

MidCap Financial Investment Cor vs MFS Municipal Income Trust — Valuation Comparison 2026

MFIC

Asset Management
MidCap Financial Investment Cor
Quality
5.9
out of 10
Value Trap
10
SAFE
Price
$10.84
Last close
Models
8/13
Active
VS

MFM

Asset Management
MFS Municipal Income Trust
Quality
1.7
out of 10
Value Trap
Price
$5.40
Last close
Models
10/13
Active

Model-by-Model Comparison

ModelType MFIC Fair ValueMFIC Upside MFM Fair ValueMFM Upside
Bayesian DCF Intrinsic $26.58 +120.2% $1.43 -73.5%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $3.64 -31.8%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $8.07 -25.5% $1.32 -75.3%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for MFIC vs MFM — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

MFIC vs MFM — Which Stock Is More Undervalued?

MFIC scores higher with a 5.9/10 quality rating vs MFM's 1.7/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing MidCap Financial Investment Cor (MFIC) and MFS Municipal Income Trust (MFM) across 13 institutional-grade valuation models reveals how each company's intrinsic value stacks up against its market price. CirclFi's engine processes SEC EDGAR 10-K and 10-Q filings, FRED macroeconomic data, and GDELT news sentiment to generate independent fair value estimates daily.

MFIC currently trades at $10.84 with a QOC of 5.9/10, while MFM trades at $5.40 with a QOC of 1.7/10.

Both companies are analyzed with models spanning intrinsic (Bayesian DCF, EPV), scenario-based (First Chicago), regime-switching (Markov DDM, RCMH-DCF), machine learning (ML-RIV, FTNN Topology), and ensemble methods (CUCE).